Meta-Analysis for jamovi
Applied a Cox Proportional Hazards model in Python to identify prognostic factors associated with survival in pediatric candidemia patients. Estimated hazard ratios, evaluated clinical covariates, and interpreted survival outcomes.
Publication-ready research figures from a single command: forest plots, KM curves with risk tables, PRISMA 2020, ROC with DeLong — 21 chart types, 9 journal presets, Chinese support, MIT-0
Forest plot of Cox hazard ratios, the standard way to report which factors change patient risk.
Reproducible R and Python clinical trial figure templates, synthetic teaching data, independent numerical QC, and Clinical Data Lab demos.
Modular publication-figure toolkit for single-cell, spatial and clinical omics — Python (matplotlib) + R (ggplot2). Swappable themes; every panel runs on synthetic data.
Provides biomedical plotting archetypes fully interoperable with the matplotlib API.
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